Skyline Query Processing on Interval Uncertain Data

摘要: Many recent applications involve processing and analyzing uncertain data. Recently, several research efforts have addressed answering skyline queries efficiently on massive datasets. However, the lacks methods to compute these data, where each dimension of object is represented as an interval or exact value. In this paper, we extensively study problem query based objects, which has never been studied before. We first model querying skylines Typically, address two efficient algorithms with I/O optimal for conventional constrained queries, respectively. Extensive experiments demonstrate efficiency all our proposed algorithms.